EECS students, postdocs, alumni, and faculty were front and center at the 28th USENIX Security Symposium in Santa Clara last week.  In addition to the Test of Time and Distinguished Paper Awards (see below), Keynote Speaker Alex Stamos (B.S. '01), previously the Chief Security Officer of Facebook, highlighted the threat model work of current ICSI postdoc Alisa Frik (advisor: Serge Egelman).  Alumnus Nicholas Carlini (Ph.D. '18, advisor: David Wagner) gave a talk on his neural networks research which was co-authored by CS Prof. Dawn Song and postdoc Chang Liu.  ICSI researchers Primal Wijesekera and Serge Egelman, and former ICSI postdoc Joel Reardon, were awarded a Distinguished Paper Award for "50 Ways to Leak Your Data: An Exploration of Apps' Circumvention of the Android Permissions System." Grad students Frank Li (advisor: Vern Paxson) and Nathan Malkin (advisors: Serge Egelman and David Wagner), received a Distinguished Paper award at the SOUPS '19 technical session for "Keepers of the Machines: Examining How System Administrators Manage Software Updates For Multiple Machines." The Zip Bomb research of alumnus David Fifield (Ph.D. '17, advisor: Doug Tygar) was also awarded a Best Paper award at the WOOT '19 technical session.

Two CS grad students, co-advised by David Culler and Raluca Popa, also made presentations.  Sam Kumar presented "JEDI: Many-to-Many End-to-End Encryption and Key Delegation for IoT" and Michael P. Andersen presented "WAVE: A Decentralized Authorization Framework with Transitive Delegation."

Graduate student Grant Ho and his co-advisors Profs. Vern Paxson and David Wagner, were honored with a Distinguished Paper Award at the 2019 USENIX Security Symposium for "Detecting and Characterizing Lateral Phishing at Scale".  In the paper, they presented "the first large-scale characterization of lateral phishing attacks, based on a dataset of 113 million employee-sent emails from 92 enterprise organizations."  Ho, Paxson, and Wagner previously won the same award at the 2017 USENIX Security Symposium for their paper "Detecting Credential Spearphishing Attacks in Enterprise Settings."

A viral real-time AI art application, co-created by three current and former graduate students of CS Prof. Alexei Efros, has won two coveted awards--Best in Show and Audience Choice--at the SIGGRAPH 2019 Real-Time Live Competition.  The interactive application, called GauGAN, was co-created by Ph.D. candidate Taesung Park during a summer internship at NVIDIA, along with alumni and NVIDIA researchers Jun-Yan Zhu (Ph.D. '17,  ACM SIGGRAPH Outstanding Doctoral Disseration winner) and Ting-Chun Wang (Ph.D. '17), as well as NVIDIAs Ming-Yu Liu.  GauGAN is the first semantic image synthesis model that can turn rough sketches into stunning, photorealistic landscape scenes.

CS graduate student Shruti Agarwal and her thesis advisor Prof. Hany Farid have created a new weapon in the war against "deepfakes," the hyper-realistic AI-generated videos of people appearing to say and do things they never actually said or did.  The new forensic technique, which uses the subtle characteristics of how a person speaks to recognize whether a new video of that individual is real, was presented this week at the Computer Vision and Pattern Recognition conference in Long Beach.  “The basic idea is we can build these soft biometric models of various world leaders, such as 2020 presidential candidates," said Farid, "and then as the videos start to break, for example, we can analyze them and try to determine if we think they are real or not.”

According to Crunchbase News,  UC Berkeley graduated 108 startup founders--not including business school graduates --who raised $1M or more after May 1, 2018.   This makes Berkeley the top-ranked public university, and the third-ranked university of any kind after Stanford and MIT, in founding graduates.  In the Crunchbase tally of all funded founders graduating from public universities (including those with business school degrees), Berkeley (with 240) had more than three times the number of funded founders than second-ranked UCLA (with 85).  Berkeley News notes that you would have to combine the second- through fifth-ranked schools (UCLA, Michigan, Illinois and Washington)  to get to Berkeley’s level. “Berkeley is the original question-the-status-quo, do-disruptive-thinking place,” says Caroline Winnet of Berkeley SkyDeck. “I like to say that we don’t just think outside the box. There is no box.”

A paper written by recent graduate Elizaveta Tremsina (B.S. '19 CS/Physics/Applied Math) has taken third place in the undergraduate category of the 2019 ACM Student Research Competition (SRC) Grand Finals.  The paper, titled "Your Story Recorded in a Magnet: Micromagnetic Simulations of Spin-Orbit Torque in Multi-layer Structures," was a continuation of the first place poster she presented at the 2018 Richard Tapia Celebration of Diversity in Computing.    "I am extremely thankful to the Berkeley EECS department for the amazing 4.5 years and for the unique chance to participate in cutting-edge research with Dr. Salahuddin's group and also attend the Tapia conference (my first one back in 2016 and last year)," she said. "I hope that more Berkeley undergrads participate in this competition in the future, be it at Tapia or other ACM conferences."  Tremsina was presented with her award at the ACM awards banquet last weekend.

A paper co-authored by freshly minted alumnus Tianshi Wang (Ph.D. '19, winner of the 2019 EECS David Sakrison Memorial Prize for "truly outstanding research") and Prof. Jaijeet Roychowdhury has won Best Paper Award at the International Conference on Unconventional Computation and Natural Computation (UCNC) 2019.  The paper, titled "OIM: Oscillator-based Ising Machines for Solving Combinatorial Optimisation Problems" will be presented at the conference in Japan next week.

Moses Surumen, who graduated with a degree in EECS this week, has been sharing his knowledge with peers in Kenya for the past two years, helping them develop the skills to solve challenges back home.  Surumen, who has 10 siblings, grew up in Kajiado, a Masai area south of Nairobi.  In 2017, he implemented a program called M-Soma, running a six-week summer course for Kenyan high school graduates in computer science.  “We were building skills the way Berkeley does, providing the best skeletal code for setting up the platform and building onto that several features they wanted to use,” he explains.  Surumen has accepted a position at Qualcomm but plans to continue to explore how to scale his project to work in different African countries.

Recent graduate Chelsea Finn (Ph.D. '18, advisors: Pieter Abbeel and Sergey Levine), has won the prestigious ACM Doctoral Dissertation Award. This award is presented annually to "the author(s) of the best doctoral dissertation(s) in computer science and engineering."  In her dissertation, "Learning to Learn with Gradients," Finn introduced algorithms for meta-learning that enable deep networks to solve new tasks from small datasets, and demonstrated how her algorithms can be applied in areas including computer vision, reinforcement learning and robotics.  Finn  is currently a research scientist at Google Brain, a post-doc at the Berkeley AI Research Lab (BAIR), and an acting assistant professor at Stanford.  Last year's recipient, Aviad Rubinstein, was also a Berkeley EECS alum.

CS graduate students Caroline Lemieux (adviser: Koushik Sen) and Daniel Fried (adviser: Daniel Klein) have won 2019 Google PhD Fellowships.  The Google PhD Fellowship Program was created to recognize outstanding graduate students doing exceptional work in computer science and related research areas.  Fellowships are awarded to students who "represent the future of research" in those fields. Lemieux, who won in the field of Programming Technology and Software Engineering, has interests which center around improving, or helping developers to improve, the correctness, reliability, and understanding of software systems.  Fried, who won in the Natural Language Processing category,  is interested in grounding language in perception and interaction, and in structured prediction.